README.md

metadata

library_name: transformers
license: apache-2.0
base_model: arielb30/opus-finetuned-kde4-en-to-he
tags:
  - translation
  - generated_from_trainer
datasets:
  - kde4
metrics:
  - bleu
model-index:
  - name: opus-finetuned-kde4-en-to-he
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: kde4
          type: kde4
          config: en-he
          split: train
          args: en-he
        metrics:
          - name: Bleu
            type: bleu
            value: 25.199843224388957

opus-finetuned-kde4-en-to-he

This model is a fine-tuned version of arielb30/opus-finetuned-kde4-en-to-he on the kde4 dataset. It achieves the following results on the evaluation set:

• Loss: 1.3339
• Model Preparation Time: 0.0033
• Bleu: 25.1998

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Bleu
1.1721	1.0	2355	1.3879	0.0033	20.0577
1.0577	2.0	4710	1.3612	0.0033	24.5566
1.0224	3.0	7065	1.3488	0.0033	24.8552
0.954	4.0	9420	1.3403	0.0033	23.3328
0.9574	5.0	11775	1.3339	0.0033	24.1134

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1